# Hardware Trojan Detection through Information Flow Security Verification

arXiv: https://arxiv.org/abs/1803.04102 · HTML: https://mlsanity.com/paper/1803.04102/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Mar 2018.

## Built on by (most cited first, 6 of 6)

- [SV-LLM: An Agentic Approach for SoC Security Verification using Large Language Models](https://mlsanity.com/paper/2506.20415/) (2025)
- [Golden Reference-Free Hardware Trojan Localization using Graph Convolutional Network](https://mlsanity.com/paper/2207.06664/) (2022)
- [TrojanWhisper: Evaluating Pre-trained LLMs to Detect and Localize Hardware Trojans](https://mlsanity.com/paper/2412.07636/) (2024)
- [A Survey and Perspective on Artificial Intelligence for Security-Aware Electronic Design Automation](https://mlsanity.com/paper/2204.09579/) (2022)
- [Automated Hardware Trojan Insertion in Industrial-Scale Designs](https://mlsanity.com/paper/2511.08703/) (2025)
- [Evil from Within: Machine Learning Backdoors through Hardware Trojans](https://mlsanity.com/paper/2304.08411/) (2023)

## Abstract (arXiv)

Semiconductor design houses are increasingly becoming dependent on third party vendors to procure intellectual property (IP) and meet time-to-market constraints. However, these third party IPs cannot be trusted as hardware Trojans can be maliciously inserted into them by untrusted vendors. While different approaches have been proposed to detect Trojans in third party IPs, their limitations have not been extensively studied. In this paper, we analyze the limitations of the state-of-the-art Trojan detection techniques and demonstrate with experimental results how to defeat these detection mechanisms. We then propose a Trojan detection framework based on information flow security (IFS) verification. Our framework detects violation of IFS policies caused by Trojans without the need of white-box knowledge of the IP. We experimentally validate the efficacy of our proposed technique by accurately identifying Trojans in the trust-hub benchmarks. We also demonstrate that our technique does not share the limitations of the previously proposed Trojan detection techniques.